1. Field
The disclosure relates generally to a computer implemented method, a computer program product, and a data processing system for strategies to backup business critical data. More specifically, The disclosure relates generally to a computer implemented method, a computer program product, and a data processing system for strategies to backup business critical data in conformance with service level agreements in terms of backup coverage, frequency of backup, mode of backup and periodic testing of backup with service provider in a service provider-managed model of backup-recovery.
2. Description of the Related Art
Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.
Characteristics are as Follows:
On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service's provider.
Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).
Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).
Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.
Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service.
Service Models are as Follows:
Software as a Service (SaaS): the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.
Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations.
Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).
Deployment Models are as follows:
Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.
Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.
Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.
Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).
A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure including a network of interconnected nodes.
Based on the sensitivities to downtime, as defined by restore point objectives and restore time objectives of service level agreements, organizations apply different strategies to backup business critical data. Even though, exact data protection strategies may vary, good data protection (backup) must be a universal part of an overall risk management strategy. A service provider-managed model of backup-recovery also defines service level agreements in terms of backup coverage, frequency of backup, mode of backup and periodic testing of backup with service provider.
Testing of backup is a very critical part of the complete data protection ecosystem. Testing of backup, such as the validation of integrity of backup image, is performed to test the quality and completeness of the backup images. However, this particular aspect of testing often gets low priority. Hardware and software resources are often unavailable. Skills required to perform the testing effectively are labor intensive, and often either intrusive/non-intrusive due to regulations that apply on the data. Sampling from numerous backups and scheduling the testing procedure also hamper and delay backup testing.
Premium service level agreements require data protection service providers periodically sample and test-restore backup images. This process ensures multiple objectives. The backup is ensured to be completed successfully in reality irrespective of the status reported by data protection software. The backup is ensured to be restorable from application perspective, such as for a database if both data and logs were backed up together consistently. Furthermore, the backup provides insight into the exact Recovery Time Objective the environment is expected to achieve.